U.S. patent application number 12/720420 was filed with the patent office on 2010-09-09 for case image registration apparatus, method and recording medium, and case image search apparatus, method, recording medium and system.
This patent application is currently assigned to FUJIFILM Corporation. Invention is credited to Masahiro Akimaru, Masahiro Endo, Hiroyoshi Furukawa, Ryuji HISANAGA, Akira Oosawa, Ken Yamaguchi.
Application Number | 20100228727 12/720420 |
Document ID | / |
Family ID | 42679132 |
Filed Date | 2010-09-09 |
United States Patent
Application |
20100228727 |
Kind Code |
A1 |
HISANAGA; Ryuji ; et
al. |
September 9, 2010 |
CASE IMAGE REGISTRATION APPARATUS, METHOD AND RECORDING MEDIUM, AND
CASE IMAGE SEARCH APPARATUS, METHOD, RECORDING MEDIUM AND
SYSTEM
Abstract
Case images are registered so as not to cause bias (or
partiality or imbalance) in amounts of feature of the case images
included in a database of a similar image search system for image
diagnosis. Since registration of the case images to the database is
controlled according to degrees of similarity of the amounts of
feature, it is possible to prevent a lot of similar case images
from being included in the search result. Thus, it is possible to
reduce possibility of representing a similar search result which
may interfere with an accurate diagnosis by a diagnostician.
Inventors: |
HISANAGA; Ryuji;
(Ashigarakami-gun, JP) ; Oosawa; Akira;
(Ashigarakami-gun, JP) ; Furukawa; Hiroyoshi;
(Sunto-gun, JP) ; Endo; Masahiro; (Sunto-gun,
JP) ; Akimaru; Masahiro; (Sunto-gun, JP) ;
Yamaguchi; Ken; (Sunto-gun, JP) |
Correspondence
Address: |
SUGHRUE MION, PLLC
2100 PENNSYLVANIA AVENUE, N.W., SUITE 800
WASHINGTON
DC
20037
US
|
Assignee: |
FUJIFILM Corporation
Tokyo
JP
SHIZUOKA PREFECTURE
Shizuoka-city
JP
|
Family ID: |
42679132 |
Appl. No.: |
12/720420 |
Filed: |
March 9, 2010 |
Current U.S.
Class: |
707/723 ;
382/218; 707/769; 707/E17.03 |
Current CPC
Class: |
G06T 2207/30004
20130101; G06T 7/33 20170101; G16H 50/70 20180101; G16H 30/20
20180101 |
Class at
Publication: |
707/723 ;
382/218; 707/769; 707/E17.03 |
International
Class: |
G06F 17/30 20060101
G06F017/30; G06K 9/68 20060101 G06K009/68 |
Foreign Application Data
Date |
Code |
Application Number |
Mar 9, 2009 |
JP |
2009-055622 |
Claims
1. A case image registration apparatus comprising: a determination
unit which compares case information corresponding to an object
image, which is a case image to be determined whether registration
to a database is required or not, and an amount of feature of the
object image, with case information corresponding to a registered
image, which is a case image other than the object image and has
been registered in the database, and an amount of feature of the
registered image, and determines whether to register the object
image in the database or not according to a result of the
comparison; and a registration unit which registers the object
image when the determination unit determines to register the object
image in the database.
2. The case image registration apparatus according to claim 1,
further comprising a degree of similarity calculation unit which
calculates a degree of similarity between the amount of feature of
the object image and the amount of feature of the registered image,
wherein the determination unit determines whether to store the
object image in the database or not according to the comparison of
the degree of similarity with a prescribed registered determination
threshold.
3. The case image registration apparatus according to claim 2,
further comprising a registration determination threshold
calculation unit which calculates the prescribed registration
determination threshold using a function whose variable is the
total number of the case images registered in the database.
4. The case image registration apparatus according to claim 2,
further comprising an item determination unit which collates the
case information corresponding to the object image and the case
information corresponding to the registered image with each other
on an item by item basis, and determines whether the number of
matching items in the collation exceeds a prescribed number
threshold or not, wherein the degree of similarity calculation
unit, when the item determination unit determines that the number
of matching items having exceeds the prescribed number threshold,
calculates the degree of similarity between the amount of feature
of the object image and the amount of feature of the registered
image.
5. The case image registration apparatus according to claim 4,
wherein the item of the case information includes at least any one
of: information pertaining to a patient including the name, sex,
age and other information of the patient; information pertaining to
imaging including a type of an imaging apparatus, an imaging
condition and other information; information pertaining to
diagnosis including a finding, a disease name and other
information; a lesion position; and an anatomic position of the
lesion position.
6. The case image registration apparatus according to claim 1,
wherein the object image is the case image inputted from an imaging
apparatus or the case image having been registered in the
database.
7. The case image registration apparatus according to claim 6,
wherein the registration unit deletes any one of the registered
image and the object image when the object image is the case image
having been registered in the database.
8. A case image search apparatus comprising a search unit which
compares a first amount of feature, which is an amount of feature
corresponding to an image to be diagnosed with a second amount of
feature corresponding to a case image in a database which has been
registered by the case image registration apparatus according to
claim 1, and searches the database for a case image having an
amount of feature similar to the first amount of feature based on a
result of the comparison.
9. The case image search apparatus according to claim 8, wherein
the search unit compares only the second amount of feature
corresponding to an image which has determined to register in the
database by the determination unit, with the first amount of
feature.
10. The case image search apparatus according to claim 8, further
comprising an output unit which outputs the case image retrieved by
the search unit.
11. A case image search system comprising: a case image
registration apparatus according to claim 1; and a case image
search apparatus which comprises a search unit which compares a
first amount of feature, which is an amount of feature
corresponding to an image to be diagnosed with a second amount of
feature corresponding to a case image in a database which has been
registered by the case image registration apparatus, and searches
the database for a case image having an amount of feature similar
to the first amount of feature based on a result of the
comparison.
12. A case image registration method performed by one or more
computers, comprising the steps of: comparing case information
corresponding to an object image, which is a case image to be
determined whether registration to a database is required or not,
and an amount of feature of the object image, with case information
corresponding to a registered image, which is a case image other
than the object image and has been registered in the database, and
an amount of feature of the registered image; determining whether
to register the object image in the database or not according to a
result of the comparison; and registering the object image in the
database based on a result of the determination.
13. A recording medium on which a program is recorded, the program
comprising computer-executable instructions of: comparing case
information corresponding to an object image, which is a case image
to be determined whether registration to a database is required or
not, and an amount of feature of the object image, with case
information corresponding to a registered image, which is a case
image other than the object image and has been registered in the
database, and an amount of feature of the registered image;
determining whether to register the object image in the database or
not according to a result of the comparison; and registering the
object image in the database based on a result of the
determination.
14. A case image search method performed by one or more computers,
comprising the steps of: comparing a first amount of feature, which
is an amount of feature corresponding to an image to be diagnosed
with a second amount of feature corresponding to a case image in a
database which has been registered by the case image registration
method according to claim 12; and searching the database for a case
image having an amount of feature similar to the first amount of
feature based on a result of the comparison.
15. A recording medium on which a program is recorded, the program
comprising computer-executable instructions of: comparing a first
amount of feature, which is an amount of feature corresponding to
an image to be diagnosed with a second amount of feature
corresponding to a case image in a database which has been
registered by the case image registration method according to claim
12; and searching the database for a case image having an amount of
feature similar to the first amount of feature based on a result of
the comparison.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Field of the Invention
[0002] The presently disclosed subject matter relates to a
technique that retrieves and presents a case image similar to a
diagnostic object image (image of object to be diagnosed) on the
basis of an amount of feature (feature amount) extracted from the
diagnostic object image.
[0003] 2. Description of the Related Art
[0004] In Japanese Patent Application Laid-Open No. 2004-5364, an
ROI (region of interest) is specified on image data; information
such as image data which has a similar feature and a diagnostic
result of the similar image data are retrieved from a database and
displayed.
[0005] In Japanese Patent Application Laid-Open No. 2001-117936, a
region of interest is extracted from a diagnostic image, and a
similarity search is performed using the amount of feature of the
region of interest.
[0006] Japanese Patent Application Laid-Open No. 2008-257292 shows
another example of similar image search system.
[0007] Japanese Patent Application Laid-Open No. 2008-245719 shows
an example of a technique for extracting a lesion region on the
basis of position information of a region of interest.
[0008] T. F. Cootes, G. J. Edwards, and C. J. Taylor "Active
Appearance Models", In Proc. 5th European Conference on Computer
Vision, Springer Germany, volume II: pp. 484-498 (1998), shows a
method of acquiring shape information and texture information of a
lesion part in the ROI (region of interest).
SUMMARY OF THE INVENTION
[0009] In an image search system for image diagnosis according to
the conventional technique, when a bias (or partiality or
imbalance) occurs between data in a database and distribution of
the amount of feature, the bias may adversely affect diagnosis of
doctors. For example, for lungs, when an image search (image
retrieval) is performed for a benign lesion such as inflammation
whose feature in the image is similar to pulmonary cancer cases
through a database including extremely many pulmonary cancer cases
whose amounts of feature are similar to each other, most of cases
obtained by the retrieval as being very similar to the benign
lesion are pulmonary cancer cases. Therefore, when a doctor with
inadequate experience uses that retrieval result to diagnose the
case, the usage of the retrieval result prevents him/her from
adequately diagnosing an inflammation even though the doctor
suspects an inflammation before the retrieval.
[0010] In addition, in a case of collecting data of various types
of image findings sharing the name of disease (disease name), such
as pulmonary adenocarcinoma, when the disease name, or
adenocarcinoma, is used as a criteria, image findings with the
similar amounts of feature may be gathered. As a result, if 90% or
more of the cases have the similar amounts of feature even with
collection of 100 adenocarcinoma cases, accuracy of similarity
search for adenocarcinoma on the residual 10% of adenocarcinoma
cases is decreased, thereby adversary affecting the diagnosis of
doctors.
[0011] The presently disclosed subject matter can register case
images so as not to cause a bias (or partiality or imbalance) in
amounts of feature of case images included in a database for a
similar image search system for image diagnosis.
[0012] A case image registration apparatus according to the
presently disclosed subject matter includes: a determination unit
which compares case information corresponding to an object image,
which is a case image to be determined whether registration to a
database is required or not, and an amount of feature of the object
image, with case information corresponding to a registered image,
which is a case image other than the object image and has been
registered in the database, and an amount of feature of the
registered image, and determines whether to register the object
image in the database or not according to a result of the
comparison; and a registration unit which registers the object
image when the determination unit determines to register the object
image in the database.
[0013] Preferably, the case image registration apparatus further
includes a degree of similarity calculation unit which calculates a
degree of similarity between the amount of feature of the object
image and the amount of feature of the registered image, and the
determination unit determines whether to store the object image in
the database or not according to the comparison of the degree of
similarity with a prescribed registered determination
threshold.
[0014] Preferably, the case image registration apparatus further
includes a registration determination threshold calculation unit
which calculates the prescribed registration determination
threshold using a function whose variable is the total number of
the case images registered in the database.
[0015] Preferably, the case image registration apparatus further
includes an item determination unit which collates the case
information corresponding to the object image and the case
information corresponding to the registered image with each other
on an item by item basis, and determines whether the number of
matching items in the collation exceeds a prescribed number
threshold or not, and the degree of similarity calculation unit,
when the item determination unit determines that the number of
matching items having exceeds the prescribed number threshold,
calculates the degree of similarity between the amount of feature
of the object image and the amount of feature of the registered
image.
[0016] Preferably, the item of the case information includes at
least any one of: information pertaining to a patient including the
name, sex, age and other information of the patient; information
pertaining to imaging including a type of an imaging apparatus, an
imaging condition and other information; information pertaining to
diagnosis including a finding, a disease name and other
information; a lesion position; and an anatomic position of the
lesion position.
[0017] Preferably, the object image is the case image inputted from
an imaging apparatus or the case image having been registered in
the database.
[0018] Preferably, the registration unit deletes any one of the
registered image and the object image if the object image is the
case image having been registered in the database.
[0019] A case image search apparatus according to the presently
disclosed subject matter includes a search unit which compares a
first amount of feature, which is an amount of feature
corresponding to an image to be diagnosed with a second amount of
feature corresponding to a case image in a database which has been
registered by the case image registration apparatus according to
claim 1, and searches the database for a case image having an
amount of feature similar to the first amount of feature based on a
result of the comparison.
[0020] Preferably, the search unit compares only the second amount
of feature corresponding to an image which has determined to
register in the database by the determination unit, with the first
amount of feature.
[0021] Preferably, the case image search apparatus further
comprises an output unit which outputs the case image retrieved by
the search unit.
[0022] A case image search system according to the presently
disclosed subject matter includes: the case image registration
apparatus described above; and a case image search apparatus which
comprises a search unit which compares a first amount of feature,
which is an amount of feature corresponding to an image to be
diagnosed with a second amount of feature corresponding to a case
image in a database which has been registered by the case image
registration apparatus, and searches the database for a case image
having an amount of feature similar to the first amount of feature
based on a result of the comparison.
[0023] A case image registration method performed by one or more
computers according to the presently disclosed subject matter, the
case image registration method, includes the steps of: comparing
case information corresponding to an object image, which is a case
image to be determined whether registration to a database is
required or not, and an amount of feature of the object image, with
case information corresponding to a registered image, which is a
case image other than the object image and has been registered in
the database, and an amount of feature of the registered image;
determining whether to register the object image in the database or
not according to a result of the comparison; and registering the
object image in the database based on a result of the
determination.
[0024] A recording medium, on which a program causing one or more
computers to perform the case image registration method is
recorded, is also included in the presently disclosed subject
matter.
[0025] A case image search method performed by one or more
computers according to the presently disclosed subject matter,
includes the steps of: comparing a first amount of feature, which
is an amount of feature corresponding to an image to be diagnosed
with a second amount of feature corresponding to a case image in a
database which has been registered by the case image registration
method described above; and searching the database for a case image
having an amount of feature similar to the first amount of feature
based on a result of the comparison.
[0026] A recording medium, on which a program causing one or more
computers to perform the case image search method is recorded, is
also included in the presently disclosed subject matter.
[0027] According to the presently disclosed subject matter, since
the registration of the case images to the database is controlled
according to the degrees of similarity of the amounts of feature,
it is possible to prevent a lot of similar case images from being
included in the search result. Thus, it is possible to reduce
possibility of representing a similar search result which may
interfere with an accurate diagnosis by a diagnostician.
BRIEF DESCRIPTION OF THE DRAWINGS
[0028] FIG. 1 is a schematic configuration diagram of a similar
case image search system;
[0029] FIG. 2 is a block diagram showing a registration unit in
detail;
[0030] FIG. 3 is a flowchart for explaining a registration process;
and
[0031] FIG. 4 is a diagram showing an example of a determination
criterion.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0032] FIG. 1 is a schematic configuration diagram of a similar
case image search system 100 according to a preferred embodiment of
the presently disclosed subject matter. This system includes an
image data input unit 1, an image analysis unit 2, a similar image
search unit 3, an image information DB 4, a display unit 5, and a
registration unit 6. The similar case image search system 100 may
be configured with a computer (including: circuits required for
operational processing such as a CPU, RAM and ROM, a data recording
medium, a data input and output circuit, a display circuit, an
operation device, and a communication circuit).
[0033] The each block of the similar case image search system 100
may integrally be configured in one computer. Instead, the similar
case image search system 100 may be configured such that the blocks
are configured with separate computers and the computers are
connected to each other via a network. The image analysis unit 2,
the similar image search unit 3 and the registration unit 6 may be
replaced with program modules (stored in a computer readable medium
such as a ROM) to be performed on a computer; special hardware
configurations are not necessarily required. The display unit 5 may
be configured with a liquid crystal display. The image information
DB 4 may be configured with a hard disk, for example.
[0034] The image data input unit 1 inputs diagnostic object images
(query images), such as a CT (Computer Tomography) image, an MRI
(Magnetic Resonance Imaging) image, a PET (Positron Emission
Tomography) image, an X ray image (including a CR (Computed
Radiography) image), a US (ultrasonic) image, an endoscopic image,
a mammography image, and a pathological image. The image data input
unit 1 can input supplementary information, such as the image size
and the imaged date and time, and case information, along with
these query images. Communication protocols between the image data
input unit 1 and a medical diagnostic imaging apparatus and formats
of the query images and the supplementary information are compliant
with a prescribed standards such as a DICOM (Digital Imaging and
Communication in Medicine).
[0035] The image analysis unit 2 analyzes a query image inputted
from the image data input unit 1, and creates an amount of feature
(a first amount of feature) required to retrieve similar images
accumulated in the image information DB 4. A method for creating
the amount of feature is performed in a similar manner to that of
an image analysis unit 21, which will be described later.
[0036] The similar image search unit 3 compares the first amount of
feature created by the image analysis unit 2 and the amount of
feature (second amount of feature) of case image accumulated in the
image information DB 4 with each other, and calculates a degree of
similarity therebetween. The second amount of feature has been
created beforehand from the case image according to a method which
is the same as the calculation method adopted in the image analysis
unit 2, and accumulated. The similar image search unit 3 specifies
the case image corresponding to the second amount of feature whose
similarity with information on the amount of feature of the query
image is the highest among the entire case images accumulated in
the image information DB 4 or the case images corresponding to a
part designated beforehand from the operation device. The similar
image search unit 3 then displays, on the display unit, 5 the
specified case image and the various types of case information
which is accumulated in the image information DB 4 and
corresponding to the case image.
[0037] The display unit 5 may be replaced with another output
device other than the image output device. For example, the
specified case image and the various types of information
corresponding to the case image, which are accumulated in the image
information DB 4, may be outputted by a printing device, instead of
the display unit 5 or along with the display unit 5. If a search
result is not image information, the result can be outputted by
synthesized voice output and the like from an audio output device.
Instead, the output device may be a network I/F, and the search
result may be outputted to a desired communication terminal (a
personal computer, a cellular phone, a PDA (Personal Digital
Assistance), etc.).
[0038] The image information DB 4 includes case information having
case images to be search object images. Here, the case information
may be stored in a manner classified according to diseases.
Further, statistical information and disease information on a
disease-by-disease basis, and disease information of an error-prone
disease and medical information with respect to a specific disease
may be linked and stored.
[0039] The case information also includes text-based diagnostic
information such as diagnostic reports created by radiologists in
addition to the case image of each definitely diagnosed
disease.
[0040] The statistical information on a disease-by-disease basis
includes, for example, following information: [0041] degree of
similarity of a representative case (the highest similarity in a
disease); [0042] average degree of similarity; [0043] total number
of registered cases of the disease concerned in a case DB; [0044]
the number of registered cases similar to the representative cases
(case patterns); [0045] characteristics of the case pattern . . .
leading symptoms; [0046] characteristics of patients in the case
pattern . . . average age, medical history, history of smoking,
etc.; [0047] national and regional morbidity rate; and [0048]
miscellaneous.
[0049] The image information DB 4 includes the amounts of feature
(second amount of feature) extracted from lesion parts of
respective registered case images. However, if the case image
itself is stored in the image information DB 4, the second amount
of feature can be acquired by subsequently analyzing the case image
by the image analysis unit 2 or the like. Accordingly, registration
of the second amount of feature in the image information DB 4 is
not necessarily required to implement of the presently disclosed
subject matter.
[0050] The display unit 5 may display statistic information such as
search result of similar images on a disease-by-disease basis from
similar images in the database, in addition to the image data with
a high degree of similarity.
[0051] The case image to be registered in the image information DB
4 by the registration unit 6 can be acquired by means of imaging
apparatuses (CT apparatus, MRI apparatus, PET apparatus, X-ray
apparatus, US apparatus, endoscope, mammography apparatus, camera
for a microscope, etc.) as with a query image. The second amount of
feature corresponding to the case image registered in the image
information DB 4 by the registration unit 6 is acquired by the
image analysis similar to that in the image analysis unit 2. The
case information corresponding to the case image registered in the
image information DB 4 by the registration unit 6 is acquired by a
user's input operation via an operation device and the like. In
this embodiment, the registration unit 6 performs registration so
as not to cause a bias (or partiality or imbalance) in the amount
of feature of the image data included in the image information DB
4.
[0052] FIG. 2 shows the registration unit 6 in detail. The
registration unit 6 includes the image analysis unit 21 and a DB
analysis unit 22. The image analysis unit 21 includes a region of
interest extraction unit 23 and a feature amount converter 24. The
respective blocks of the registration unit 6 may integrally be
configured into a computer. Instead, the registration unit 6 may be
configured such that the blocks are configured with separate
computers and the computers are connected to each other via a
network. The DB analysis unit 22, the region of interest extraction
unit 23 and the feature amount converter 24 may be replaced with
program modules (stored in a computer-readable recording medium
such as a ROM) to be performed on a computer; special hardware
configurations are not necessarily required.
[0053] The image analysis unit 21 inputs desired case images, such
as a CT image, an MRI image, a PET image, an X ray image (including
a CR image), an US (ultrasonic) image, an endoscopic image, and a
pathological image, as registration candidate images. The image
analysis unit 21 also inputs case information corresponding to
registration candidate images.
[0054] The region of interest extraction unit 23 extracts a part to
be retrieved, or the region of interest, such as a lesion, organ or
the like included in the case image, from the inputted registration
candidate images. A method for extracting the region of interest is
arbitrary. For example, a publicly known image processing technique
using features of contours, pixel values and position information
of an image, such as automatic extracting methods of Japanese
Patent Applications Laid-Open Nos. 2004-5364 and 2001-117936, and a
method for extracting a region on the basis of the position
information of the region of interest of Japanese Patent
Application Laid-Open No. 2008-245719 and the like, may be used.
The extraction of the region of interest is not necessarily full
automatic. Instead, the extraction may semi-automatically be
performed by an image processing technique that uses features in
proximity to a region designated through an operation device by the
user.
[0055] Next, the feature amount converter 24 calculates the amount
of feature on an extracted region extracted by the region of
interest extraction unit 23. The amount of feature to be calculated
may be an amount of feature pertaining to pixel values such as the
average, the variance, the maximum value, the minimum value and the
luminance histogram of image data, and/or the amount of feature
pertaining to the shape such as the position of the extracted
region, the roundness of the extracted region, the moment, the
radius of a section, the volume and the area. In addition thereto,
the feature amount may be shape information and/or texture
information of the lesion in the ROI (region of interest) acquired
by "Active Appearance Models" (T. F. Cootes et al). Instead,
information temporarily registered in the image information DB 4
may be processed using a prescribed mathematical expression (e.g.,
principal component analysis and independent component analysis)
and the obtained value may be adopted as the amount of feature.
[0056] The DB analysis unit 22 determines whether the registration
candidate image is to be registered in the image information DB 4
or not, on the basis of the amounts of feature of the registration
candidate images calculated by the feature amount converter 24 and
the amounts of feature of case images accumulated in the image
information DB 4. The DB analysis unit 22 registers the
registration candidate image in the image information DB 4 or
discards the image without registration according to the
determination result.
[0057] More specifically, the DB analysis unit 22 performs a
registration process as shown in FIG. 3.
[0058] In step S1, the DB analysis unit 22 compares the case
information (determination criterion) corresponding to any one of
case images having already been registered in the image information
DB 4 and the case information (registration candidate case
information) corresponding to the registration candidate image with
each other, and determines whether both are identical with each
other or not. FIG. 4 shows an example of the determination
criterion. The criterion includes: information pertaining to a
patient, such as the name, age and sex of the patient; information
pertaining to imaging, such as the type (CT, MRI, etc.) and the
model number of the apparatus used for imaging and an imaging
condition; information pertaining to the definite diagnosis such as
the finding, the disease name and the others; the purpose of
imaging; the anatomic position of the lesion part; and the part of
the lesion (organ), which are indicated by report information
stored in a header and the like of the image data. Determination
(Matching) of identity between the determination criterion and the
registration candidate case information is performed with respect
to respective items included in the case information. In addition
thereto, presence or absence of a certain qualification (a
certified physician or a specialist physician) of the person who
has registered the diagnostic information, the volume of report
information, the imaging date and time of the image, the
registration date and time of the case information and the like may
also be adopted as the determination criterion.
[0059] Based on the result of the matching in step S1, in step S2,
the DB analysis unit 22 counts the number of items whose contents
are determined to be identical in step S1. If the number exceeds a
first threshold designated beforehand by a user's operation via the
operation device, the registration candidate image corresponding to
the registration candidate case information is determined as a
registration analysis object image; the processing proceeds to step
S3. Here, a registration analysis object image means an image which
is to be analyzed in order to determine whether the image is to be
registered in the image information DB 4.
[0060] For example, when the threshold=3, and if case information
of a certain determination criterion and case information of the
registration candidate case information are identical all in the
age of the patient, the imaging condition and the anatomic
position, the registration candidate image corresponding to the
registration candidate case information is determined as a
registration analysis object image.
[0061] However, if at least the disease name included in the
determination criterion and the disease name included in the
registration candidate case information are identical with each
other, the registration candidate image is unconditionally
determined as the registration analysis object image; the
processing proceeds to step S3. This is for eliminating redundant
registration of the image with the same disease name and the
similar image finding.
[0062] In analogous terms, if at least the disease name included in
the determination criterion and the disease name included in the
registration candidate case information are not identical with each
other, the registration candidate image is unconditionally
determined as an image to be registered. In this case, step S3 is
omitted and the processing proceeds to step S4.
[0063] In step S3, the DB analysis unit 22 calculates a degree of
similarity between the amount of feature of the registration
analysis object image calculated by the feature amount converter 24
and the amount of feature of the case image corresponding to the
case information storing the determination criterion identical with
the registration analysis object image. The feature amount
converter 24 may omit an analysis of an image other than the
registration analysis object image. A publicly known method, for
example a difference of values of the amounts of feature and the
least squares methods in a feature space (a weighted space is
acceptable), may be adopted as a method for calculating the degree
of similarity. For the sake of convenience of illustration, the
degree of similarity S is defined by the following mathematical
expression (mathematical expression descried in the paragraph 0048
of Japanese Patent Application Laid-Open No. 2008-257292). Note
that implementation of the presently disclosed subject matter does
not limit the calculation norm of the degree of similarity S to
this definition.
S = i = 1 n wi Mi - mi [ Expression 1 ] ##EQU00001##
[0064] The amount of feature m.sub.i (i=1, 2, . . . , n) is the
amount of feature of the registered case image. M.sub.i (i=1, 2, .
. . , n) is the amount of feature extracted from the registration
analysis object image. w.sub.i (i=1, 2, . . . , n) is a weighting
coefficient corresponding to each amount of feature having been
defined beforehand, on disease-by-disease basis. Numerical
subscript "i" of m.sub.i, M.sub.i and w.sub.i designates a
coordinate in a feature amount space. The more similar both amounts
of feature, the smaller the value of the degree of similarity S
becomes; the more different both amounts of feature, the larger the
value of the degree of similarity S becomes.
[0065] Preferably, in step S1, if the disease name included in the
determination criterion and the disease name included in the
registration candidate case information are identical and the parts
and the anatomic positions of lesion are both identical, the
registration candidate image may be unconditionally determined as
the registration analysis object image. In this case, it is
possible to prevent the amounts of feature of parts irrelevant to
each other from being compared in step S3. For example, if the
amount of feature m.sub.i (i=1, 2, . . . , n) extracted from the
registration analysis object image is a value (n-dimensional
multi-valued data) pertaining to a lung area S1 (the part and the
analytical position), the feature amount M.sub.i (i=1, 2, . . . ,
n) of the registered image whose degree of similarity S is to be
calculated is also a value (n-dimensional multi-valued data)
pertaining to the lung area S1.
[0066] In step S4, if the calculated degree of similarity is less
than a prescribed second threshold, the DB analysis unit 22
determines that the registration analysis object image is out of
scope of registration and does not register the image in the image
information DB 4; if the calculated degree of similarity is not
less than the prescribed second threshold, the DB analysis unit 22
determines that the registration analysis object image is the image
to be registered and registers the image in the image information
DB 4. In this case, the case information corresponding to the
register analysis object image is also registered in the image
information DB 4.
[0067] The second threshold TH is, for example, determined
according to a following mathematical expression,
TH=.alpha..times.N+.beta..
[0068] N is the total number of case images registered in the image
information DB 4. The .alpha. and .beta. are constants. The
.alpha., .beta. and/or the threshold themselves may arbitrarily be
designated by a user's input operation via the operation device.
Typically, TH=f(N). "f" is any function which tends to increase
according to increase of N. The function "f" may arbitrarily be
designated by a user's input operation via the operation device,
and the processing unit (CPU) may calculate the actual second
threshold according to the designated function.
[0069] More specifically, if the number of registered case images
is small, the second threshold becomes small and the registration
analysis object image whose degree of similarity with the
registered case image is a relatively small value (high
correlation) is registered. If number of registered case images is
large, the second threshold becomes large and the registration
analysis object image having a high correlation with the registered
case image becomes not to be registered. Instead, if the number of
registration N is less than a certain threshold (e.g., 100), the
registration analysis object image and its case information may
unconditionally be registered. That is, if the number of
registration is small, enrichment of the image information DB 4 may
take precedence.
[0070] In lieu of not registering the image determined not to be
registered, the registered image and the corresponding case image
in the image information DB 4 whose degree of similarity with the
image determined not to be registered is less than the second
threshold may be deleted, and the image determined not to be
registered and its corresponding case information may be registered
instead. This prevents the images having similar feature from being
redundant in the image information DB 4. Selection of whether the
image determined not to be registered is not actually registered or
the image is substituted for the registered case image may be
arbitrarily designated by a user's operation to the operation
device and any one of the images may be registered in the image
information DB 4 according to the designation. Instead, if the case
information of the registered case image includes information with
high precedence, such as new date and time information, report
information with high content, registration by a qualified person,
or large amount of image data, the registered case image may be
left in the image information DB 4. Conversely, if the case
information of the registered case image includes no information
with high precedence, the registered case image may be deleted from
the image information DB 4, and the image determined not to be
registered may newly be registered in the image information DB
4.
[0071] The registration candidate image is not necessarily a newly
inputted image, and may be the image arbitrarily selected from
among the case images registered in the image information DB 4. In
this case, the registration unit 6 leaves the image when it is
determined that the image is to be registered in the image
information DB 4, and deletes the image from the image information
DB 4 when it is determined that the image is not to be registered.
As with the above description, if the case information includes
information with high precedence, the case image corresponding
thereto may be left in the image information DB 4, and if the case
information does not include information with high priority, the
case image corresponding thereto may be deleted from the image
information DB 4. In other words, if there are two images whose
degree of similarity is less than the second threshold, only any
one of both may be deleted.
[0072] In general, if there are two or more images in the image
information DB 4, the degree of similarity is calculated from a
pair composed of any two different images in the image information
DB 4, and any one image of the pair is deleted according to result
of the comparison between the value of the degree of similarity and
the second threshold; if this process is comprehensively repeated
over all pairs of images in the image information DB 4, redundancy
of the similar images can be eliminated among the images having
already been registered in the image information DB 4. This may be
performed by user's designation of a command such as "refresh the
image information DB 4" through the operation device. Instead, this
may periodically be performed at a desired schedule.
[0073] In addition, an image determined not to be registered may be
registered in the image information DB 4 along with a flag
indicating that the image is determined not to be registered, and
subsequently the case image assigned with the flag is excluded from
the images to be searched by the similar image search unit 3.
Accordingly, the similar image search unit 3 retrieves similar
images only from the images without the flag. In other words, the
similar image search unit 3 compares only the second amount of
feature of the case images without the flag with the first amount
of feature.
[0074] As described above, since the registration of the case
images to the image information DB 4 is controlled according to the
degrees of similarity of the amounts of feature, it is possible to
prevent a lot of similar case images from being retrieved as the
search result. Thus, it is possible to reduce possibility of
representing a similar search result which may interfere in
diagnosis by a diagnostician.
[0075] While examples and embodiments of the presently disclosed
subject matter have been explained in detail, the presently
disclosed subject matter is not limited to the above, needless to
say, various improvements and modifications may be added without
departing from the scope of the presently disclosed subject
matter.
[0076] For example, by providing a program causing a computer to
execute the processes performed devices according to the
embodiments, recording the program on a recording medium,
installing the program on a computer using the recording medium,
and causing the computer on which the program is installed to
execute the program, it is possible to implement the devices
according to the embodiments.
* * * * *